A. Field of the Invention
The present invention is related to systems and methods for optimizing resources in a production supply chain and more particularly, to a system and method for optimizing resources such as material and human resources at any place of a supply chain or production areas by monitoring its location at the supply chain and production areas, monitoring used and available spaces and monitoring the productivity of human resources using automatic identification in order to control supply and production processes and make optimizing recommendations in real time using Evolutionary Computation and Expert systems.
B. Description of the Related Art
Over the last 20 years, the Automation and Information Technologies have impacted the Supply Chain in such way that coordination, operation and communication have improved significantly, reducing cost for errors or for not having visibility. Nevertheless, there are still many opportunities to improve the way it is working now since there is still a misconnection in the real operation at the very bottom level at every single activity between Workers, tools/Machinery and Products upon the time.
These misconnections mean different things depending on the step in the supply chain being analyzed. For example: In the day to day operations in a Manufacturing Plant, the lack of knowledge and understanding of what specific and unique item is crossing each work station (specific and unique item means differentiation between one can of coke and another one of the same product for example) could mean that it would be very difficult to identify a problem on the line of production exactly when it happens and even more, understand the reason of the problem by having the whole picture of people working on every work station and its correlation with other workers either in the same workstation or in other workstations, as well as the machinery/tools being used and the ones turned off, and finally the work-in process and bottle necks on the whole line of production.
Not having all this information on time could result in a wrong decision to solve a problem or not making a decision at all. On the contrary, by having these information in Real Time could mean making a decision before a problem happens. This is possible by processing data generated at the line of production on every movement. Of course, if every entity is tracked in real time, that means a huge amount of data generated on every second. In order to process these data, Information Technology Systems are needed, while in order to make decisions with this data, Evolutionary Computation is needed (area of Artificial Intelligence), and in order to learn from such decisions, Expert Systems (area of Artificial Intelligence) are used to compare new decisions suggested by the Evolutionary Computation with the results obtained from previous decisions.
A similar example is applicable in a Distribution Center where more players come to the equation like the customers urging for products, different type of tools capable of doing the same work (different capabilities of forklifts, carts, platform trucks, hand trucks and etcetera), distance form current point to destiny compared with distance for other workers to perform the same activity (cost) and other related implications. Monitoring all these entities in order to ensure a perfect and computer assisted functionality similar like the one described for a Manufacturing Plant brings the same type of solution combining real time identification technologies, Evolutionary Computation and Expert systems as well.
There have been developed systems and methods for optimizing supply chains and production lines but none of them are able to offer optimizing solution in real time based on real time information.
In view of the above, applicant developed a system and method for optimizing resources in a supply chain and production line using RFID and artificial intelligence which can be adapted to any supply chain or product line, including warehouses, and which is able to optimize a plurality of tools/machinery or processing stations, a plurality of products and even personnel in real time by analyzing real time information about said entities and historic information stored in databases about optimum decisions taken in the past by the system.
The system and method of the present invention has the following further advantages:                a Reduce chances for Human Error.        Anticipates operational problems working in preventive mode by analyzing trends in Real Time.        Optimize the usages of resources: cost, time, priorities, etc.        Makes intelligent decisions considering ALL players and their real time situation in few seconds.        Learns from Intelligent Decisions taken for making more intelligent decisions every day.        